Apparatus, System and Method for Medical Analyses of Seated Individual

ABSTRACT

Apparatus, system and method for medical analysis of a seated individual, includes determining the aortic valve opening; the PTT; and calculating the PWV. Determining the aortic valve opening includes collecting BCG data while sitting on a seat and determining the timing of the aortic valve opening, taking into account posture. Measuring the aortic pulse wave transit time includes collecting BCG data while sitting on a seat capable of measuring changes in apparent weight; determining the timing of the aortic valve opening; detecting the arrival of the pulse wave at the end point; and measuring the relative timings of the two events. Calculating the PWV includes determining a length of the arterial segment through which a pulse wave is to be measured between a start point and an end point; and dividing the determined length of the arterial segment by the PTT.

CROSS REFERENCE

This application claims the benefit of the filing date of U.S.Provisional Patent Application Ser. No. 62/183,222, filed Jun. 23, 2015,which is hereby incorporated by reference in its entirety.

FIELD

The disclosure relates to apparatus, system and method for medicalanalyses of a seated individual, and in specific instances for detectingheart function and processing signals therefrom.

BACKGROUND

Existing methods for tracking an individual's vital signs involveseither taking time out of their day to use medical devices, or wearingportable ambulatory devices. These methods are intrusive to one's dailylife, requiring one to change their lifestyle and habits in order toconsistently acquire their medical state.

Historically, there are four measurement techniques that are used forestimation of a pulse wave velocity. First, the clinical gold standarduses tonometry where a transducer is held against the carotid artery(neck) and a thigh pressure cuff is used to measure when the pulse wavereaches the femoral artery. The distance between the two measurementpoints, coupled with the pulse transit time (PTT) is used to determinean aortic pulse wave velocity (PWV) and estimate aortic compliance. Thismethod requires assistance from medically trained personnel to provideand properly attach the equipment to the patient.

In a second technique, two points on the same artery are used to measurean arterial PTT, with the distance between measurement pointsdetermining PWV. This is often done using two photoplethysmography (PPG)sensors with known separation between the two positioned on the radialartery of the arm, or in the finger (using the foot to foot measurementof the two PPG waveforms). However, this technique estimates the PWV inthe measured peripheral artery, not in the aorta, and is therefore notuseful for determining aortic compliance, but is often used to estimateblood pressure.

In a third technique, the R-wave peak of the ECG is used as the startingpoint, with a peripheral PPG measurement (often finger, toe, or ear)used as the distal point. This measurement is called the pulse arrivaltime (PAT) and is often used as a surrogate for PTT (and PWV) inestimating blood pressure. However, as this measurement techniqueincludes the PEP it has no basis in physiology and fundamental pulsewave velocity/blood pressure theory.

In a fourth technique, the BCG is used as the starting point (estimatingaortic ejection) and PPG at the periphery (toe) is used as the distalpoint for estimation of a PWV. This approach measures an averaged PWV ofthe aorta and femoral artery. It has been used for aortic complianceestimation. However, it is not an accurate measurement of the true aortaPWV due to the contribution of the femoral artery distance from the endof the aorta to the toe.

Chair-based approaches for recording BCG are known to produce waveformsfor the same person that are significantly different for varioussegments of the same recording, severely reducing the diagnostic valueof the measurement. Body movements are known to generate stronger signalvalues than normal cardiac activities during recording causing loss ofinformation and destroying individual BCG cycles.

Currently, the art lacks integration of physiological monitoring into anindividual's everyday life without causing them to change their habitsor perform any specific task. The art further lacks health conditionmonitoring techniques that provide a robust measure of aortic PWVwithout the aid of medical personnel for collection of data. The artlacks the ability for the daily non-invasive medical analysis of thecardiac and vascular functions of an individual.

SUMMARY

In accordance with one aspect of the present disclosure a method fordetermining the aortic valve opening of a seated individual includesrecording the BCG of the individual while sitting on a seat having aforce sensor capable of measuring changes in the apparent weight of theseated individual; and detecting a location on the recorded BCG waveformor its transforms representing the aortic valve opening indicatingventricular ejection and the origination of a pulse wave taking intoaccount the posture of the seated individual.

In accordance with another aspect the present disclosure furtherincludes determining the PTT of the seated individual by determining thetime of aortic valve opening; detecting the arrival of the initiatedpulse wave at the end point while sitting on the seat; and measuring therelative timings of the two events.

In accordance with another aspect the present disclosure furtherincludes calculating the PWV of the seated individual by dividing thedetermined length of the arterial segment by the pulse transit time fromthe initiation at the start point to the detection at the end point ofthe pulse.

In accordance with another aspect of the present disclosure a method formedical analysis of a seated individual includes collecting BCG dataover time from the individual while sitting on a seat comprising atleast one force sensor capable of measuring changes in the apparentweight of the seated individual; and determining the timing of theaortic valve opening from the BCG data taking into account the anglebetween the seat platform and the torso of the seated individual.

In accordance with another aspect of the present disclosure a method formedical analysis of a seated individual further includes determining aselected end point along a length of artery from the aortic valve;detecting the arrival of the pulse wave initiated by the aortic valveopening at the selected end point along the artery while sitting on theseat; and determining the PTT of the seated individual by measuring therelative timings of the aortic valve opening and the arrival of thepulse wave at the selected end point

In accordance with another aspect of the present disclosure a method formedical analysis of a seated individual further includes determining alength of the arterial segment between the aortic valve and the selectedend point along the artery through which the pulse wave is measured andcalculating the PWV of the seated individual by dividing the determinedlength of the arterial segment by the PTT

In accordance with another aspect of the present disclosure a method formeasuring physiological changes associated with a simulated Valsalvamaneuver includes determining a length of an arterial segment along anartery from the aortic valve through which a pulse wave is to bemeasured between a start point representing the aortic valve opening andan end point; during a BM detecting the aortic valve opening indicatingventricular ejection of the origination of a pulse wave by recording thebBCG of the individual while sitting on a toilet seat having a forcesensor capable of measuring changes in the apparent weight of the seatedindividual, wherein the toilet seat is secured to a toilet; detectingthe arrival at the end point of the initiated pulse wave of theindividual while sitting on the toilet seat; measuring the relativetimings of the two events; and determining at least one physiologicalcondition of the individual associated with the simulated Valsalvamaneuver.

These and other aspects of the present disclosure will become apparentupon a review of the following detailed description and the claimsappended thereto.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be more completely understood in consideration of thedetailed description of various embodiments of the disclosure thatfollows in connection with the accompanying drawings, in which:

FIG. 1 illustrates a top view of an integrated toilet seat in accordancewith an embodiment of the present disclosure;

FIG. 2 illustrates a bottom view of an integrated toilet seat inaccordance with an embodiment of the present disclosure;

FIG. 3 is a diagram depicting the aorta and associated arteries of anindividual illustrating starting and ending locations for themeasurement of PTT in accordance with an embodiment of the presentdisclosure;

FIG. 4 is a diagram depicting various posture positions of a seatedindividual;

FIG. 5 illustrates an exploded view of a non-load bearing floating hingein accordance with an embodiment of the present disclosure;

FIG. 6 illustrates an exploded view of a floating/sealed standoff and aperspective view illustrating a partial cut-away of a portion of theassembled floating/sealed standoff in accordance with an embodiment ofthe present disclosure;

FIG. 7 is a graph of various waveforms generated from a seatedindividual in an upright position in accordance with an embodiment ofthe present disclosure;

FIG. 8 is a graph of various waveforms generated from a seatedindividual in a leaning position in accordance with an embodiment of thepresent disclosure; and

FIG. 9 is a schematic of a BCG force sensor in accordance with anembodiment of the present disclosure.

DETAILED DESCRIPTION

The present disclosure relates to a system, method, and apparatus forthe non-invasive medical analysis of an individual in a sittingposition. Various embodiments illustrate the usefulness of applicationfor daily non-invasive medical analysis of cardiac and vascularfunctions. An embodiment of the present disclosure includes thenon-invasive medical analysis of an individual in a sitting position.BCG data is extracted from a seated individual. A suitable seat is incommunication with instrumentation to extract BCG data, such as a BCGwaveform, from the seated individual. A suitable seat includes a toiletseat integrated with such instrumentation. While the present disclosureis not necessarily limited to the embodiments shown herein, variousaspects of the disclosure may be appreciated by those of skill in theart.

Keys to successful monitoring and early detection of changes associatedwith emerging or deteriorating health conditions include ensuringpatient compliance, daily measurement, and consistent physiologicalstate at the time of measurement. An embodiment of the system includesan integrated seat capable of inconspicuous daily monitoring of cardiacand vascular functions through methods including the ECG, BCG, and PPGfrom the buttocks or upper thigh (bECG, bBCG, and bPPG) and a basestation for collection of data. In an embodiment, the seat containssensors, microprocessor, wireless communication capabilities, and canharvest energy from the environment with techniques such as RF energyharvesting with a rectenna based system providing a self-containedbioinstrumentation system that automatically captures medically relevantdata daily. Instruments such as ECG require skin contact to achieverobust measurement and can further ensure fine features of the waveformare accurately captured. Sensors which do not require skin contact arealso suitable for use in the present disclosure. Additionally, thepressure associated with daily bowel movements provides opportunitiesfor monitoring associated physiological differences between the restingstate and the pressure state. Biometric analysis (e.g., ECG-based) canbe used to discriminate between subjects. Data collected by the systemcan be used in conjunction with other bathroom and home environmentalsensors to provide a broad picture of health-relevant activities andstressors.

An embodiment of the system includes a self-contained seat containingenergy storage, such as a rechargeable or non-rechargeable battery. Amicroprocessor can provide full system control including powermanagement, data capture, analysis and storage, and wirelesscommunication with the base station. The base station for collection ofdata may be a stand-alone system or part of a larger home environmentalmonitoring system.

The following abbreviations and definitions are used throughout thedisclosure:

-   ECG—Electrocardiogram.-   PPG—Photoplethysmogram.-   BCG—Ballistocardiogram.-   bBCG—BCG is the measurement of the BCG of an individual while in the    sitting position.-   bPPG—PPG is the measurement of the PPG of an individual while in the    sitting position.-   bECG—ECG is the measurement of the ECG of an individual while in the    sitting position.-   PTT—Pulse transit time (travel time of pressure wave in the arterial    segment length of interest).-   PEP—Pre-ejection period (isovolumetric contraction of the ventricle;    time between ECG Q-wave and opening of aortic valve).-   PAT—Pulse arrival time (PEP+PTT).-   PWV—Pulse wave velocity (arterial segment length divided by PTT).-   BP—Blood pressure.-   BM—Bowel movement.-   IPG—Impedance plethysmogram.-   LVET—Left ventricular ejection time.

In accordance with an embodiment of the present disclosure a method formedical analysis of a seated individual includes collecting BCG dataover time and determining the timing of the opening of the aortic valvefrom the BCG data taking into account posture. In an embodiment, themethod further includes selecting an end point along a length of arteryfrom the aortic valve and determining the timing of a pulse waveinitiated by the aortic valve opening reaching the end point. In anembodiment, measuring the aortic pulse wave velocity of an individualincludes determining the length of the arterial segment between theaortic valve and the selected ending point through which the pulse waveis to be measured. The aortic valve opening indicates ventricularejection of blood and the origination of a pulse wave associated withthe ejection. This origination signal can be detected, for example, byrecording the BCG of the individual while sitting on a surface incommunication with a sensor capable of measuring changes in the apparentweight of the seated individual. These forces act to dynamicallyincrease or decrease the load on the sensors and are typically in the 1Newton range. A signal representing the arrival of the initiated pulsewave of the seated individual at the selected end point can be detected,for example, by a sensor positioned under the buttocks or upper thigh ofthe individual. The relative timings of the two signals can be measured,the difference being the PTT. The aortic pulse wave velocity iscalculated by dividing the determined length of the arterial segmenttraveled by the pulse wave by the transit time from the initiation tothe detection of the pulse wave, i.e., from the selected starting pointto the selected ending point.

The BCG data can be represented as the BCG waveform, or a transformedBCG such as the 1^(st), 2^(nd), 3^(rd) etc. derivatives or integrals.The shape of the bBCG waveform measured in accordance with the presentdisclosure is affected by the posture of the seated individual.Therefore, it is important to be able to determine the location on thewaveform that represents the opening of the aortic valve taking intoaccount the posture or changes in posture of the seated individual.Optionally, an ECG can be used to determine a window in the bBCGwaveform that contains the location of the starting point, i.e., theinitiation of the pulse wave. The origination of the pulse wave can bedetermined in accordance with the present disclosure while accountingfor posture.

An embodiment of the disclosure includes an integrated toilet seatplaced on a standard toilet. Sensor systems can be integrated within thetoilet seat to monitor the following: Ballistocardiogram (BCG)—measuressmall changes in an individual's apparent weight due to the mechanicalmotion of the heart; Photoplethysmogram (PPG)—an optical measure of thechange in blood volume in localized tissue; Electrocardiogram (ECG)—ameasure of the electric activity of the heart; SpO_(2;) body weight; andbody temperature.

An embodiment of the system can enable a broad range of dailymeasurements extracted from the bECG, bBCG, and bPPG including: heartrate; heart rate variability; left ventricular ejection time; pulsetransit time based on ECG R-wave or the BCG ejection (correlation tovascular compliance); blood pressure; cardiac output; cardiaccontractility; abnormal heart function or issues with autonomic nervouscontrol of the heart (Valsava maneuver); blood oxygenation (SpO₂ viafiltered PPG sensors); respiration rate (IPG or PPG); stress levels(e.g., via heart rate variability); body weight; body temperature; QTinterval (time between Q and T waves of the ECG); QRS duration (timefrom the Q wave to the T wave); PTT; PWV; PAT; LVET; and PEP.

In an embodiment, a standoff is a component that supports the seat on abase surface. The load is supported by the standoff and a sensor can beintegrated with the standoff by which static and dynamic loads can bemeasured. In one embodiment, the integrated toilet seat has a pluralityof standoffs that support the seat on the toilet surface and a pair ofnon-load bearing floating hinges that allow the entire seat to movevertically in both directions (e.g., up and down). This ensures eachstandoff is in contact with the toilet surface and can produce accuratereadings from a sensor associated with the standoff.

Each standoff can have an integrated force sensor or plurality of forcesensors associated with the standoff, which can measure both thesubject's weight and small apparent changes in the subject's weight(e.g., measurement of the bBCG). The standoff can be a floating sealedassembly. In one embodiment, the bBCG is measured by a plurality ofindependent sensors (one in each standoff) positioned in a mannersufficient to determine the initiation of a pulse wave from ventricularejection of blood from the heart regardless of the posture of anindividual sitting on the integrated toilet seat. In one embodiment, thebBCG is measured with four independent sensors (one in each standoff),however other configurations can be used, such as three independentsensors (one in each standoff) (e.g., with one or two sensors on therear standoffs), or more. Suitable sensors are capable of measuring asmall change in force for monitoring the bBCG and include piezoresistive sensors, piezoelectric elements, strain gauges, or the like.

The PPG can be measured at a distal point, such as the toe or finger.For example, the PPG can be measured by an optical sensor, whichtypically is composed of an LED light source and a photodetector,located on the surface of the toilet seat positioned under the seatedindividual's buttock or upper thigh. In another embodiment, the PPG canbe measured at the individual's toe from a mat or other device. The LEDlight source is typically green, red or IR. The photodetector istypically a photodiode or a phototransistor. The resulting waveformshows how the local blood volume changes due to the pumping of theheart, as seen in the image shown in FIGS. 7 and 8.

The ECG instrument can be positioned on the surface of the toilet seatso as to be in contact with the seated individual's skin. Typically, anECG instrument is composed of at least three electrodes. Two of theelectrodes are used for a differential measurement, while the third is areference electrode. The reference electrode is typically driven eitherwith the common mode signal of the other two electrodes, or a fixedreference voltage, or is referenced to ground through an impedancenetwork. The ECG instrument may also be composed of only twodifferential leads.

A method for determining the aortic valve opening of a seated individualincludes recording the BCG of the individual while sitting on a seathaving a plurality of standoffs resting on a support surface and havinga force sensor capable of measuring changes in the apparent weight ofthe seated individual integrated into at least one of the plurality ofstandoffs; and detecting a location on the BCG data representing thesignal of the aortic valve opening indicating ventricular ejection ofthe origination of a pulse wave taking into account the posture of theseated individual.

A method for measuring the aortic pulse wave transit time of a seatedindividual includes determining a length of the arterial segment throughwhich a pulse wave is to be measured between a start point representingthe aortic valve opening and a selected end point along the arterialsegment; recording the BCG of the individual while sitting on a seathaving a force sensor capable of measuring changes in the apparentweight of the seated individual integrated into at least one of aplurality of standoffs, wherein the standoffs are resting on a supportsurface; detecting a location on the BCG data representing the aorticvalve opening indicating ventricular ejection of a pulse wave at thestart point of the seated individual; detecting a signal representingthe arrival of the initiated pulse wave of the individual at the endpoint while sitting on the seat; and measuring the relative timings ofthe two events to determine the pulse transit time from the initiationat the start point to the detection at the end point of the pulse.

FIG. 1 illustrates a top view of an integrated toilet seat in accordancewith an embodiment of the present disclosure. FIG. 2 illustrates abottom view of an integrated toilet seat in accordance with anembodiment of the present disclosure.

Aortic compliance and blood pressure of an individual can be derivedfrom the Pulse Wave Velocity (from bBCG to bPPG). In an embodiment, thedisclosure includes a method for the measurement of the PWV of anindividual sitting on the integrated toilet seat.

The aortic PWV can be calculated by determining the length of thearterial segment divided by the pulse transit time (PTT) over thatlength. The velocity is the distance divided by the time. The PTT isdetermined by the start of ventricular ejection (when the aortic valveopens), as well as the point in time when the pulse wave reaches the endpoint, for example, as shown in FIG. 3.

The BCG data can be used to determine when the heart valve opens. Thestart of the PTT can be identified, for example, on the BCG waveform.The PPG measures the change in local blood volume so a PPG sensorpositioned under the buttocks of the seated individual can determine theend point of the PTT based on the onset of the PPG.

The pulse transit time is calculated directly by taking the differencein time between the PPG beat onset, and the aortic valve opening (AV),determined from the BCG data, as shown in the following formula.

PTT=Δt_(BCC→PPG) =t _(PPG) −t _(AV)

The length of the arterial segment can be determined by various methods,including direct subject measurement on a user by user basis. However,it is possible that the length can be estimated without directmeasurement by using population statistics. This is the measureddistance the pulse wave travels during the PTT. The aortic pulse wavevelocity (PWV) is this distance (d_(artery)) divided by the PTT as shownin the following formula.

${PWV} = \frac{d_{artery}}{PTT}$

The PAT is a summation of the PEP and the PTT. The PEP starts at thebeginning of ventricular contraction and ends with the start ofventricular ejection (when the aortic valve opens). The pulse transittime begins when the aortic valve opens and ends when the pressure wavereaches the distal measurement point. For blood pressure and aorticcompliance, the ideal distal location is the end of the aorta, close tothe start of the femoral artery.

The present disclosure provides a more accurate determination of aorticPWV using the bBCG (aortic valve opening—start of ventricular ejection)to a bPPG measured at the buttocks (close to the end of the aorta) ascompared to prior disclosures. Thus, this measurement is dominated bythe aorta characteristics, providing the most accurate estimate ofaortic compliance and aortic blood pressure. This approach removesinaccuracies induced by measurement in the periphery, and by referencingthe R-wave peak of the ECG.

Aortic compliance and blood pressure estimates can be based on thecalculated PWV in accordance with the present disclosure usingclassical/clinically accepted standards.

In addition to measuring the BCG from the force sensors, the seat canalso be used to estimate a user's weight. When a user sits on the seat,a certain percentage of their weight is on their feet. This percentagewill be different based on body type and posture. If the user is leaningforward and resting their arms on the knees, a larger percentage oftheir weight will be on their feet. With respect to an integrated seat,since it is self-contained it can measure the weight present on theseat. Estimating or determining a user's seated posture is important foraccurately estimating the user's weight. Machine learning can be used toestimate both posture and weight from the independently measured forcesensors.

Thus, in an embodiment wherein the seat has a plurality of standoffsresting on a support surface it is important that the load present onthe seat is only carried by the standoffs. The use of a floating hingeor pair of floating hinges to connect the seat to a toilet is an exampleof an embodiment which ensures that none of the load is present on thehinge, which could negatively impact the measurement accuracy and signalquality of both weight and BCG.

Direct integration of the BCG sensors into the seat's standoffs allowsfor complete integration of sensors into a standard seat. This is oneway that such a technology is most likely to be adopted by users. Thisdiffers from similar devices that present a custom platform underneathan entire toilet, or additional legs/platform to carry the weight fromthe seat to a scale that surrounds the toilet.

One of the challenges of integrating the sensors into the standoff isthat the standoff preferably translates all force to the BCG sensor andnowhere else. Furthermore, the standoff cannot bind; otherwise the BCGsignal can be lost. FIG. 6 illustrates a floating/sealed standoffassembly in accordance with an embodiment of the present disclosure.This design incorporates a gasket encircling the standoff which mateswith a retainer and urethane seal to fix the standoff to a cavity in theseat to accomplish these goals. Additionally, the standoffs arepreferably waterproof and cleanable. This results in a system that iscompletely transparent to the end user. It is also important to notethat any shape standoff can be used with this method.

Existing prior art BCG sensors and scales utilize sensor bridges tocapture the BCG waveform. The bridge configuration is used to increasethe signal to noise ratio and sensitivity of the sensor. This is verycommon in scales and other sensor systems. The downside of using asensor bridge is that there is only one signal output for all fourstandoffs which does not allow for each standoff to be measuredindependently. While this allows for accurate BCG measurements underideal circumstances (e.g., user standing upright on a scale whileremaining perfectly still), it cannot be used to reliably measure theBCG of an individual sitting, for example on a toilet seat. The user'sseated posture can impact the signal quality of the BCG and the waveformshape, as can motion artifacts.

In accordance with the present disclosure, separate BCG sensors can beused for each standoff. By measuring each sensor independently, thepresent method can use algorithms to estimate the posture and extract amore accurate and reliable BCG. This not only can improve the BCG signalquality, but it can also make the measurement more repeatable. This isan important feature of the embodiment since BCG force translation tothe sensors changes based on the user's posture.

The use of multiple, e.g., four, independent sensors enable posturedetermination to assist in accurate determination of weight. As posturechanges from an upright to leaning over position, more weight is carriedby the feet to the floor. This is important for monitoring weightchanges over time, especially for heart failure patients where rapidweight gain (water retention) is a predictive indicator of declininghealth.

Traditional prior art weight systems combine all force sensors into asingle signal, such as with a Wheatstone bridge. Combining the signalsin the analog domain reduces motion artifacts and increases signal tonoise ratio (“SNR”). However, this results in a loss of postureinformation that is important in the present disclosure for accurateweight and BCG waveform analysis. In accordance with an embodiment ofthe present disclosure, rather than using a Wheatstone bridge, eachsensor signal is captured independently and combined in software(utilizing posture information) to reduce motion artifacts and increaseSNR. Combining four independent BCG channels into a single BCG signaluses the average between the four channels. Beat averaging can be usedto further reduce noise, using the ECG R-wave peak for beat-to-beatfeature alignment.

In accordance with an embodiment of the present disclosure, a pair ofno-load bearing floating hinges allows the BCG to be measured with anintegrated system in the toilet seat. A standard toilet seat has twohinges on the back of the seat that connects the seat and the lid to thetoilet bowl. The BCG is stronger on the rear standoffs, as shown bysubject testing. If part of the load on the seat were carried by thehinges, the BCG quality would significantly decrease. By removing thehinges as a load bearing point, two rear standoffs can be used tocapture the majority of the BCG signal. A floating hinge also allows formore accurately estimating a user's weight, since the hinges bear noneof the load.

In one embodiment shown in FIG. 5, the floating hinge works by having anelongated slot that allows the entire seat to travel vertically in bothdirections. Note that the seat cover is still connected to the hinge inthe standard way and is not floating independently from the seat. It isalso important that the hinge design does not allow horizontal motion.This may exacerbate motion artifacts and can negatively impact theuser's experience.

The BCG signature is impacted by posture since the force vector relativeto gravity is changed. The difference between two postures, sittingupright and leaning forward are shown in FIGS. 7 and 8 along with asingle R-R interval on the ECG. The morphology of each BCG signalchanges with posture. Determination of posture based on, for example,analysis of the independent sensor readings is important to properinterpretation of the BCG waveform.

In an embodiment, determining weight and posture from BCG sensorreadings includes the following steps: preprocessing of sensor readings,including mean reduction, scaling, data transformation to adjust forskewness in data; exploring higher order relations between sensorreadings and output (weight); performing linear regression forestimating weight, and logistic regression for predicting posture on atraining dataset containing sensor readings and subjects' weight andposture. In both regressions, all of the four sensor readings, sensorinteraction terms and higher order features (as explored in the previousstep) are fed to the regression block for accurate estimation of weightand posture.

An embodiment of the present disclosure provides the automaticintegration of a simulated Valsalva maneuver with BM. The Valsalvamaneuver, where a subject forcedly exhales against a fixed pressure (orby keeping the mouth and nose closed), induces a transient increase inintra-thoracic pressure that can provide estimates of changes in bothstroke volume and pre-ejection period based on ECG and BCG measures. Alack of change in stroke volume during this strain phase of the Valsalvamaneuver has been observed in patients with pulmonary congestion andreduced left ventricular ejection fraction suggesting potential forearly detection with routine monitoring. Additionally, the Valsalvamaneuver may also be useful in evaluating the risk of ventriculartachyarrhythmias and the efficacy of drug treatment in patients withlong-QT syndrome.

By integrating cardiac instrumentation with a toilet seat, cardiacmeasurements can be captured during a BM. When the user is strainingduring a BM, it is very similar to the Valsalva maneuver, and thus,provides a simulated Valsalva maneuver.

Methods for Determination of Aortic Valve Opening from the BCG forDifferent Postures.

The BCG can be measured from a plurality of sensors in a seat. Thestatic signal from each sensor can be used to determine posture of thesubject. For example, higher relative signals on the forward sensors isindicative of the subject leaning forward, with the ratio of the forwardto back sensors indicative of the posture angle. In another example, thesubject height, weight, age and/or gender are used in conjunction withthe static signals for a more accurate determination of posture. Inanother example, statistical analysis (e.g., machine learning) ofsignals gathered at different postures across a population can be usedto provide a posture estimate from the obtained signals.

Posture can also be determined by additional methods including userentry of posture (e.g., position 1, 2, or 3 representing angles ofapproximately 90 degrees, 60 degrees, or 45 degrees); a video camera andimage processing to determine torso outline and relative angle betweentorso and legs; and a distance sensor integrated into the toilet seatcover. The waveform characteristics of the average BCG signal can beused to determine posture. During a training phase, data can becollected with subjects in different known postures. Waveformcharacteristics associated with each posture can be determined and usedfor future posture determination based on average BCG waveform analysis.

Posture information can be used to determine temporal segments forspecific BCG analysis where the subject has consistent posture. Aorticvalve opening is then determined from a combination of the dynamic BCGsignal and the subject posture.

In an embodiment, the specific BCG waveform feature to be extracted isposture dependent. In an upright posture (alpha approx. 90°) aorticvalve opening is associated with the first upward peak of the BCGwaveform from the beginning of the cardiac cycle as shown in FIG. 7, byway of example only. In a leaning forward position (alpha approx. 50°)aortic valve opening is associated with the first downward peak of theBCG waveform from the beginning of the cardiac cycle as shown in FIG. 8,by way of example only. Other features or posture-dependent fractionaldistances between neighboring features may also be used. The specificBCG features can be from the BCG waveform, or from a transformed BCGsuch as the 1^(st), 2^(nd), 3^(rd), etc. derivatives or integrals.

In another embodiment, a leaning forward BCG waveform is transformed toan upright BCG waveform based on posture. Posture is the angle from theseat platform to the torso of a seated individual. The BCG waveform isdetermined for the y and z directions as shown in FIG. 4. A model isgenerated for transformation of these primary waveforms to a newwaveform consistent with a potential posture (alpha dependent). Thismodel uses vector analysis of force transformations and superposition tocreate the new waveform. In another embodiment, torque is incorporatedinto the model based on subject height, weight, age and/or gender and anestimate of the location of the heart. The inverse model is applied tothe captured BCG dynamic signals based on determined posture to createan equivalent upright waveform. The upright waveform feature recognitionis applied to the equivalent upright waveform to determine aortic valveopening.

In another embodiment, the features to be extracted are determined bysimultaneous BCG measurements with a gold-standard aortic valve openingmeasurement. A database containing correlation of the angle between theseat and the torso of a seated individual with the bBCG datacorresponding to the opening of the aortic valve can be established. Thecorrelation of specific BCG features to aortic valve opening can bedetermine for a range of postures, resulting in a database such as alookup table indicating which feature should be chosen based on thecurrent posture of the seated individual. In one example, the lookuptable can be created for a population (e.g., entire population, healthypopulation, heart failure population, etc.) using statistics from aposture study across the desired population. In another example, this isdone on a population with key features classified according to subjectheight, weight, age and/or gender. In another example, the lookup tablecan be created for each individual subject based an individualizedfeature correlation to aortic valve opening on a per-subject basis.

This table can be created by correlating specific BCG features directly(or with a time offset) to the simultaneous aortic valve opening goldstandard measurement. The time offset could be a constant, or anequation based on physiologic intervals such as heart rate, or acombination of the two. The specific BCG features can be from the BCGitself, or from a transformed BCG such as the 1^(st), 2^(nd), 3^(rd),etc. derivatives or integrals. The subject sits on the seat containingthe BCG sensors while measuring the time of aortic valve opening. Thiscan be repeated for multiple postures (from upright to full leaningforward as when resting elbows on knees) with known angles between thetorso and the seating platform. In one example, the time of aortic valveopening can be determined through transthoracic echocardiographycaptures of pulse wave Doppler, tissue strain, and aortic valve imagingmeasured simultaneously and time synchronized with the BCG. In anotherexample, the time of aortic valve opening can be determined using a timesynchronized measure of impedance cardiography. In a third example, thetime of aortic valve opening can be determined using an aortic flow ratesensor measuring the start of systolic ejection, when time synchronizedwith the BCG. The gold-standard and BCG waveforms can be timesynchronized through acquisition through the same data acquisitionsystem, application of a third signature that is picked up in both thegold-standard and BCG waveforms, or by using a surrogate reference pointfor both measures such as the ECG R-wave.

The time corresponding to a specific BCG waveform feature can bedetermined for each posture. In one example, this is done on a beat bybeat basis and the results averaged. In another example, the waveform isfirst normalized to account for different R-R intervals (heart ratevariability), and then the BCG (and ECG) beat waveforms are averaged tocreate an average waveform before extracting the feature time points.This information can be used to create the aforementioned lookup table,which can be used to determine the time of aortic valve opening usingthe BCG.

Method for Determination of the PPG Feature for Pulse Wave Arrival inthe PTT Calculation.

A plethysmograph is obtained on the individual at a distal point todetermine changes in blood volume or pressure associated with arrival ofthe pressure wave associated with ventricular ejection. In one examplethis is done optically using a photodiode and an emitter(photoplethysmogram or PPG). In another example, impedance techniquesare used to locally determine changes in blood volume. In anotherexample, a pressure or force sensor is used in a tonometry mode todetect pulse arrival.

The time based waveform is analyzed to extract the time of a specificwaveform feature. In one example, this is the onset of the wave (orfoot) as shown in FIG. 7, although other features may be used. Otherfeatures or fractional distances between neighboring features may alsobe used. Features associated with the derivatives (e.g., 1^(st), 2^(nd),3^(rd), etc.) of the PPG waveform may also be used. In one example, thisis done on a beat by beat basis and the results averaged. In anotherexample, the waveform is first normalized to account for different R-Rintervals (heart rate variability), and then the PPG (and ECG) beatwaveforms are averaged to create an average waveform before extractingthe feature time points.

Method for Determination of the PWV Based on the BCG and PPG Waveforms.

The length of the artery from the aortic valve to a selected end pointalong the artery (AL) can be determined based on direct subjectmeasurement (external). Measurements are done on an individual in aseated position. The distance between the sternal notch (SN) and thesternal angle (SA) is measured, either directly or by reference to theseating platform top (B). The distance between sternal angle (SA) andaortic valve (AV) is measured, e.g., via ultrasound imaging. Thedistance between sternal notch and aortic arch (AA) is measured, e.g.,via ultrasound imaging. The approximate artery length (AL) is calculatedusing the following equation:

AL=[AV to AA distance]+[AA to B distance]

AL≈[(SA−AV)+(SN−SA)−(SN−AA)]+[(SN−B)−(SN−AA)]

In another embodiment, population statistics based on height, weight,age and/or gender are used in place of a subject specific measurement.The time difference between the aortic valve opening feature on the BCGwaveform and the pulse arrival feature on the distal PPG waveformdetermines the pulse transit time (PTT). The aligned BCG and PPGwaveform extracted time points can be used directly, or each can bereferenced to the ECG R-wave. The pulse wave velocity (PWV) iscalculated by dividing the AL by the PTT.

The disclosure will be further illustrated with reference to thefollowing specific examples. It is understood that these examples aregiven by way of illustration and are not meant to limit the disclosureor the claims to follow.

EXAMPLES

The following experimental protocol, conditions and instrumentation wereused in each of the examples. The user was instructed to remove clothingand put on a hospital gown. The user was instructed to sit on the seatwith complete skin contact. The weight, PPG, ECG, and BCG waveforms weresimultaneously captured using a NI CompactRio system with LabView for2.5 minutes. The signals were analyzed in MATLAB in order to locate thedesired features in the signal.

The BCG system uses four independent piezoresistive sensors (Flexi Forcesensors from Tekscan). The interface schematic is shown in FIG. 9. Thesignal takes two paths, one for the BCG and the other for the weight.The weight is buffered and then directly captured by the dataacquisition system. A low-pass filter is used to reduce high frequencynoise and a high-pass filter is used to remove the large DC offset dueto the subject's weight.

The PPG sensor uses an IR LED with a matched photodiode. Thephotodiode's current is converted to a voltage using a transimpedanceamplifier (TIA). The DC offset is removed and then the signal islow-pass filtered to isolate the PPG signal.

The ECG sensor has three electrodes. The two rear electrodes were usedas the inputs to a differential amplifier. The third electrode isconnected to the circuit ground and is located on the right side of theuser on the front of the seat. The instrumentation used is built intothe Biopac data acquisition system.

All of the instrumentation is captured on a LabView data acquisitionsystem. Signal processing techniques are then used to locate the BCGfeature associated with aortic valve opening. Similar techniques areused to locate the onset of the PPG waveform (this is called the PPGfoot).

Example 1 PWV Measurement of Individual Sitting in Upright Position

Determination of the PTT when a subject is in an upright sittingposition, i.e. an angle of approximately 90° between the seat platformand the torso of the subject. The following example takes place in a labsetting at room temperature with a healthy individual (subject) with nohistory of cardiovascular disease. The subject is told to sit uprightwith skin contact on a toilet seat that contains the following sensors:4 BCG channels; PPG; and ECG. The sensor locations are those shown inFIGS. 1 and 2.

A 2.5 minute long recording is captured using a National Instrumentsdata acquisition system. Each channel is captured at 1000 samples persecond and is time synchronized. Once the recording is finished, thesubject is no longer needed and the signals can be analyzed. The R-peakin each heart beat is located using a standard ECG delineation method.For example, “A Real-Time QRS Detection Algorithm” by Pan and Tompkins.In the example shown in FIG. 7 the average R-R interval was found to be0.603 seconds, resulting in a heart rate of 99.5 BPM.

A single average PPG beat is found using the following beat averagingtechnique. Each PPG beat is defined as the wave between each consecutiveR-peak. After locating each PPG beat, they are all resampled so thatthey have the same length (in this example, the length will be theaverage R-R interval multiplied by the sample rate). Once all of the PPGbeats are of the same length, they are averaged together on asample-by-sample basis. The resulting waveform is the averaged PPG beat.

The onset of the PPG (PPG foot) is determined to be the minimum of theaverage beat. A single BCG waveform is calculated from the four raw BCGchannels by simply averaging them together. This isolates the BCG in they direction when sitting upright (see FIG. 4). A single average BCG beatis determined using the same method as was done with the PPG.

The aortic valve opening is located on the BCG between the ECG Qwave andthe PPG foot. When the subject is sitting upright, the opening of theaortic valve is determined to be the first BCG peak after the Qwave.

The pulse transit time (PTT) can be calculated by finding the intervalbetween the aortic valve opening (AV_(open)) and the PPG foot(PPG_(foot)). The time difference is normalized to the R-R interval(RR_(interval)), so the actual PTT can be calculated by multiplying therelative time interval with the R-R interval.

PTT=(AV _(open)−PPG_(foot))*RR _(interval)

In this example, the PTT for sitting upright is 152 milliseconds. Thelength of the arterial segment between the aortic valve and the selectedend point (AL) was determined to be 0.94 meters. The PWV is calculatedaccording to the formula PWV=AL/PTT to be 6.18 m/s.

Example 2 PWV Measurement of Individual Sitting In Leaning ForwardPosition

Determination of the PTT when a subject is in a leaning forward sittingposition, i.e. an angle of approximately 50° between the seat platformand the torso of the subject. The following example takes place in a labsetting at room temperature with a healthy individual (subject) with nohistory of cardiovascular disease. The subject is told to sit in aleaning forward position with skin contact on a toilet seat thatcontains the following sensors: 4 BCG channels; PPG; and ECG. The sensorlocations are those shown in FIGS. 1 and 2.

A 2.5 minute long recording is captured using a National Instrumentsdata acquisition system. Each channel is captured at 1000 samples persecond and is time synchronized. Once the recording is finished, thesubject is no longer needed and the signals can be analyzed. The R-peakin each heart beat is located using a standard ECG delineation method.For example, “A Real-Time QRS Detection Algorithm” by Pan and Tompkins.In the example shown in FIG. 8 the average R-R interval was found to be0.603 seconds, resulting in a heart rate of 99.5 BPM.

A single average PPG beat is found using the following beat averagingtechnique. Each PPG beat is defined as the wave between each consecutiveR-peak. After locating each PPG beat, they are all resampled so thatthey have the same length (in this example, the length will be theaverage R-R interval multiplied by the sample rate). Once all of the PPGbeats are of the same length, they are averaged together on asample-by-sample basis. The resulting waveform is the averaged PPG beat.

The onset of the PPG (PPG foot) is determined to be the minimum of theaverage beat. A single BCG waveform is calculated from the four raw BCGchannels by averaging them together. This isolates the BCG in the ydirection when sitting upright (see FIG. 4). A single average BCG beatis determined using the same method as was done with the PPG.

The aortic valve opening is located on the BCG between the ECG Q-waveand the PPG foot. When the subject is leaning forward at an angle ofapproximately 50°, the opening of the aortic valve corresponds to thefirst trough before the main BCG peak.

The pulse transit time (PTT) can be calculated by finding the intervalbetween the aortic valve opening (AV_(open)) and the PPG foot(PPG_(foot)). The time difference is normalized to the R-R interval(RR_(interval)), so the actual PTT can be calculated by multiplying therelative time interval with the R-R interval.

PTT=(AV _(open)−PPG_(foot))*RR _(interval)

In this example, the PTT for sitting leaning forward at an angle ofapproximately 50° is 150 milliseconds. The length of the arterialsegment between the aortic valve and the selected end point (AL) wasdetermined to be 0.94 meters. The PWV is calculated according to theformula PWV=AL/PTT to be 6.27 m/s.

Example 3 Measurement of Physiological Changes Associated With a BM

The subject is instructed to take a BM while on the fully integratedtoilet seat. The interval during the BM is determined by the subject ona handheld device. The parameters that are associated with the Valsalvamaneuver, such as the QT interval, are extracted for both the BM stateand non-BM state.

Taking a bowel movement (BM) allows more advanced diagnosis on theintegrated toilet seat.

Method 1—Instructed

User is instructed to keep their mouth and nasal cavity closed whileattempting to forcedly exhale while sitting on the seat.

The Valsalva maneuver is performed for 5 seconds.

All of the signals previous mentioned are captured and analyzed.

Method 2—Automatic

User sits on the seat in their home to perform a BM.

There will be a period during BM that will be recognized as thesimulated Valsalva.

Automatic analysis will be used to determine the physiologicaldifferences between the resting state and simulated Valsalva state.

Although various embodiments have been depicted and described in detailherein, it will be apparent to those skilled in the relevant art thatvarious modifications, additions, substitutions, and the like can bemade without departing from the spirit of the disclosure and these aretherefore considered to be within the scope of the disclosure as definedin the claims which follow.

What is claimed:
 1. A method for medical analysis of a seated individualcomprising: collecting BCG data over time from the individual whilesitting on a seat comprising at least one force sensor capable ofmeasuring changes in the apparent weight of the seated individual; anddetermining the timing of the aortic valve opening from the BCG datataking into account the angle between the seat platform and the torso ofthe seated individual.
 2. The method of claim 1, further comprisingdetecting a signal representing the ECG of the individual and using thesignal to identify the window of the opening of the aortic valve on acorresponding bBCG waveform.
 3. The method of claim 1, wherein the seatcomprises a plurality of standoffs resting on a support surface and theat least one force sensor is integrated into at least one of theplurality of standoffs.
 4. The method of claim 3, wherein the pluralityof standoffs comprises at least three.
 5. The method of claim 3, whereincollecting the BCG data comprises detecting a signal from each forcesensor independently.
 6. The method of claim 1, wherein the seat is atoilet seat.
 7. The method of claim 3, wherein the seat is secured tothe support surface by a pair of no-load bearing floating hinges.
 8. Themethod of claim 7, wherein the pair of no-load bearing floating hingesallow movement of the seat in both vertical directions while restrictinghorizontal movement of the seat.
 9. The method of claim 1, furthercomprising: determining a selected end point along a length of arteryfrom the aortic valve; detecting the arrival of the pulse wave initiatedby the aortic valve opening at the selected end point along the arterywhile sitting on the seat; and determining the PTT of the seatedindividual by measuring the relative timings of the aortic valve openingand the arrival of the pulse wave at the selected end point.
 10. Themethod of claim 9, further comprising determining a length of thearterial segment between the aortic valve and the selected end pointalong the artery through which the pulse wave is measured andcalculating the PWV of the seated individual by dividing the determinedlength of the arterial segment by the PTT.
 11. The method of claim 10,wherein the length of the arterial segment is determined by directmeasurement of the individual or is estimated using populationstatistics.
 12. The method of claim 10, wherein the selected end pointalong the arterial segment is located in a portion of the buttocks orthe upper thigh.
 13. The method of claim 9, wherein the detecting thearrival of the pulse wave at the end point along the arterial segmentwhile sitting on the seat is by an optical bPPG sensor integrated on asurface of the seat.
 14. The method of claim 9, wherein the detectingthe arrival of the pulse wave at the end point along the arterialsegment while sitting on the seat is by an impedance sensor integratedon a surface of the seat.
 15. The method of claim 1, wherein the takinginto account the angle between the seat platform and the torso of theseated individual comprises creating a database containing a correlationof the angle between the seat platform and the torso of the seatedindividual with the BCG data feature corresponding to timing of theaortic valve opening; determining the angle between the seat platformand the torso of the seated individual; and identifying from thedatabase the timing of the aortic valve opening in the BCG datacorresponding to the determined angle.